Listed below are the numbers of cricket chirps in 1 minute and the corresponding temperatures in "E Find the regression equation, letting chirps in 1 minute be the independent (x) variable. Find the best predicted temperature at a time when a cricket chirps 3000 times in 1 minute, using the regression equation. What is wrong with this predicted temperature? Chirps in 1 min Temperature ("F) 955 852 1123 1246 794 835 972 912 O 79.6 74.9 815 914 66.9 755 765 76.4 The regronslon equation is y -375) ((0.0419)x (Round the y-intercept to one decimal place as needed. Round the slope to four decimal places as needed.) The best predicted temperature at a time when a cricket chirps 3000 times in 1 minute, based on the regression equation, is 163 2"F (Round to the nearest integer as needed) What is wrong with this predicted temperature? O A. The chips in 1 minute should have been the dependent variable OB. It is only an approximation An unrounded value would be considered accurate OC. It is unrealistically high The value 3000 is far outside of the range of observed values O D. Nothing is wrong with this value It can be treated as an accurate prediction

Listed below are the numbers of cricket chirps in 1 minute and the corresponding temperatures in "E Find the regression equation, letting chirps in 1 minute be the independent (x) variable. Find the best predicted temperature at a time when a cricket chirps 3000 times in 1 minute, using the regression equation. What is wrong with this predicted temperature? Chirps in 1 min Temperature ("F) 955 852 1123 1246 794 835 972 912 O 79.6 74.9 815 914 66.9 755 765 76.4 The regronslon equation is y -375) ((0.0419)x (Round the y-intercept to one decimal place as needed. Round the slope to four decimal places as needed.) The best predicted temperature at a time when a cricket chirps 3000 times in 1 minute, based on the regression equation, is 163 2"F (Round to the nearest integer as needed) What is wrong with this predicted temperature? O A. The chips in 1 minute should have been the dependent variable OB. It is only an approximation An unrounded value would be considered accurate OC. It is unrealistically high The value 3000 is far outside of the range of observed values O D. Nothing is wrong with this value It can be treated as an accurate prediction

College Algebra

7th Edition

ISBN:9781305115545

Author:James Stewart, Lothar Redlin, Saleem Watson

Publisher:James Stewart, Lothar Redlin, Saleem Watson

Chapter1: Equations And Graphs

Section: Chapter Questions

Problem 10T: Olympic Pole Vault The graph in Figure 7 indicates that in recent years the winning Olympic men’s...

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Olympic Pole Vault The graph in Figure 7 indicates that in recent years the winning Olympic men’s pole vault height has fallen below the value predicted by the regression line in Example 2. This might have occurred because when the pole vault was a new event there was much room for improvement in vaulters’ performances, whereas now even the best training can produce only incremental advances. Let’s see whether concentrating on more recent results gives a better predictor of future records. (a) Use the data in Table 2 (page 176) to complete the table of winning pole vault heights shown in the margin. (Note that we are using x=0 to correspond to the year 1972, where this restricted data set begins.) (b) Find the regression line for the data in part ‚(a). (c) Plot the data and the regression line on the same axes. Does the regression line seem to provide a good model for the data? (d) What does the regression line predict as the winning pole vault height for the 2012 Olympics? Compare this predicted value to the actual 2012 winning height of 5.97 m, as described on page 177. Has this new regression line provided a better prediction than the line in Example 2?
Table 2 shows a recent graduate’s credit card balance each month after graduation. a. Use exponential regression to fit a model to these data. b. If spending continues at this rate, what will the graduate’s credit card debt be one year after graduating?
Let X = height of the students in inches Let Y = Foot length of the students in centimeters Complete manual solutions for the SLRM coefficients, their interpretations and write down the best fitting linear regression equation. What is the predicted value of foot when height = 75?
The experimenters conducted a regression analysis on the results and made the output from the analysis publicly available on Open Science Framework (osfio/fm5c2). From this output, we can derive that regression equation shown here. The equation predicts participants' relative performance estimates (from 0% to 99%) from their scores on the measure of their theories of intelligence, while controlling their actual scores on the antoymns test. Remember: The theories of intelligence survey includes a series of statements that participants rate on a scale of 1 to 6; average scores on the overall measure range from 1, indicating views of intelligence as highly stable; to 6, indicating views of intelligence as highly changeable. Relative performance estimate = 12.10 (theories of intelligence score) +0.13 (antonyms test score). Based on this regression equation, what kind of regression analysis did the researchers perform? a. A simple linear regression analysis b. Multiple regression analysis…
A car dealer wants to estimate the price of a used car based on the age of the car and the mileage. Based on a sample of 20 cars, she determines the sample regression equation that predicts price taxes on the basis of the age (in years) of the number of miles is Price=21,510-1230Age-0.035 Miles (a) If the age of the car was fixed and the mileage was increased by 10,000, would the price increase or decrease and by how much? (b) Predict the selling price of a five-year-old car with 65,000 miles. (Round your answers to the nearest whole number.)
Listed below are systolic blood pressure measurements (in mm Hg) obtained from the same woman. Find the regression equation, letting the right arm blood pressure be the predictor (x) variable. Find the best predicted systolic blood pressure in the left arm given that the systolic blood pressure in the right arm is 80 mm Hg. Use a significance level of 0.05. -------------- on the second question, 155.2 is the right answer but I don't know how to get the answer. Could you please help me.
The least-squares regression equation is y=728.0x+14,705 where y is the median income and x is the percentage of 25 years and older with at least a bachelor's degree in the region. The scatter diagram indicates a linear relation between the two variables with a correlation coefficient of 0.8165. For every dollar increase in median income, the percent of adults having at least a bachelor's degree is ___%, on average. For a median income of $0, the percent of adults with a bachelor's degree is ____%.
At a .01 level of significance is there sufficient evidence to conclude that the number of books sold is related to the number of registered students in a straight-line manner, and give the regression equation.
The following table gives the ages of female students in school and the corresponding Body Mass index (BMI) of 8 randomly selected students.(α=0.05) Age24223032211925 BMI27283029282726 Determine whether ages and BMI are significantly related.Determine the coefficient of linear determination and Intepret.Set up a linear regression equation to predict body mass index from age of students.Predict the body mass index of student who has the age of 26 years.
The least-squares regression equation is y=784.6x+12,431 where y is the median income and x is the percentage of 25 years and older with at least a bachelor's degree in the region. The scatter diagram indicates a linear relation between the two variables with a correlation coefficient of 0.7962. Interpret the slope.
Suppose the athletic director at a university would like to develop a regression model to predict the point differential for games played by the men's basketball team. A point differential is the difference between the final points scored by two competing teams. A positive differential is a win, and a negative differential is a loss. For a random sample of games, the point differential was calculated, along with the number of assists, rebounds, turnovers, and personal fouls. Use the data in the accompanying table attached below to complete parts a through e below. Assume a = 0.05. a) Using technology, construct a regression model using all three independent variables. y = __ + (_)x1 + (_)x2 + (_)x3 + (_)x4 b) Test the significance of each independent variable using a= 0.10. c) interpret the p-value for each independent variable. d) Construxt a 90% confidence interval for the regression coefficients for each independent variable and interpret the meaning. e) Using the results from…
For the 2011 season, suppose the average number of passing yards per attempt for a certain NFL team was 6.1. Use the estimated regression equation developed in part (c) to predict the percentage of games won by that NFL team. (Note: For the 2011 season, suppose this NFL team's record was 7 wins and 9 losses. Round your answer to the nearest integer.)